Engineering Knowledge for a rule-based stop-light AI

Let's move towards another _back of the napkin_ AI system, this time let's just focus on knowledge

For this activity you will give knowledge (rules) of the AI and then go back to explaining it in terms of Goals, Environment, and Adaptation

This is meant to allow us to begin to bridge from designing independent of implementation, to designing along side implementation.

Remember, you can draw pictures/diagrams to augment your words (for the G, E, and A).

What rules would an agent use when encountering a stop-light?

 

• What might be the goals of the agent encountering a stop-light?

 

• What is the environment that our stop-light agent will be adapting within?

 

• How might the rule-based agent adapt to the stop-light? How might it's inner environment change? (We will go over this, but a little prediction/forecasting doesn't hurt)

(You can keep this high-level...)